جست‌وجوی استاد و پژوهشگر

Panos Markopoulosمشاهده پروفایل

استاد

• Ambient Intelligence
• Behavior Change Support Technology
• Sleep Quality Monitoring
• +۶ مورد دیگر

Panos Markopoulos is a Professor of Design for Behavior Change at Eindhoven University of Technology (TU/e), affiliated with the Industrial Design department. He also serves as an Adjunct Professor at the University of Technology Sydney (UTS) and a Visiting Scientist at Kemphenhaeghe Expertise Center for Epileptology, Sleep Medicine, and Neurocognition. Academic Background: Electrical Engineering (NTUA), Computer Science (Queen Mary, University of London), and Human-Computer Interaction (PhD, Queen Mary) Research Focus: Ambient Intelligence, Behavior Change Support Systems, Wearable Technology, and Child-Computer Interaction Editorial Roles: Founding Editor of Elsevier’s Journal on Child Computer Interaction, Chief Editor of Taylor & Francis’ Behavior and Information Technology His research explores adaptive persuasive systems, family-aware technologies, and user-centered design methodologies. Key publications include work on persuasion profiling, collaborative design, and evaluation frameworks for children’s interactive products. He has contributed extensively to academic literature, with notable works spanning from 2004 to 2016, emphasizing personalized user experiences, ambient intelligence, and rehabilitation technologies. His expertise bridges interaction design, behavioral science, and technological innovation for societal impact. Professional Activities: European Commission evaluator, editorial leadership in HCI Teaching: Design for Behavioral Change, Final Master Project guidance

Joshua J. Coonمشاهده پروفایل

استاد

• Bioanalytical Chemistry
• Mass Spectrometry
• Proteomics
• +۴ مورد دیگر

Joshua J. Coon is a Professor at the University of Wisconsin-Madison with appointments in the Department of Biomolecular Chemistry and the Department of Chemistry. He leads the Coon Group, focusing on advancing mass spectrometry technologies for proteomics, metabolomics, and lipidomics. His research addresses fundamental questions in cell biology, including stem cell differentiation, epigenetic regulation, and cancer biomarker discovery. Affiliations : Director of the NIGMS National Center for Quantitative Biology of Complex Systems. Research Emphasis : Instrumentation development, data analysis software, ion chemistry, and biological applications of proteomics. Laboratory : Located in the Genome Center of Wisconsin with a dozen hybrid mass spectrometers, including Orbitrap systems. Collaborations : Long-term partnership with Thermo Fisher Scientific and the Wisconsin Alumni Research Foundation (WARF) for technology commercialization. Training : Mentored 27 Ph.D. students since 2009, emphasizing interdisciplinary research and professional development.

Mahsan Nouraniمشاهده پروفایل

عضو هیئت علمی

• Artificial Intelligence
• Human-Computer Interaction
• Healthcare Informatics
• +۳ مورد دیگر

Mahsan Nourani is a Research Assistant Professor at Northeastern University, specializing in intersections of human-computer interaction, artificial intelligence, and healthcare informatics. Their research focuses on explainable AI systems, user behavior in AI partnerships, and design of interactive machine learning tools. Current work explores cognitive biases in human-AI collaboration, predictive analytics in healthcare, and activity recognition in videos. Key research areas include user profiling in AI applications, trust dynamics in intelligent systems, and visual debugging tools for machine learning models. Notable projects include the HEART initiative for real-time healthcare analytics and development of the DETOXER explanation framework for temporal classification systems. Recent publications investigate nudge techniques for behavioral change (Romadoro project), anchoring bias effects in AI system trust, and evaluation of view rotation techniques in virtual reality navigation. Their work consistently bridges technical AI advancements with human-centered design principles. No academic awards are listed in the provided materials. Current affiliations include Northeastern University's research groups in AI ethics, human-computer interaction, and healthcare technology innovation.

• Energy Efficiency in Software
• Multicore Memory Systems
• Hardware/Software Co-Design
• +۳ مورد دیگر

Arrvindh Shriraman is an Associate Professor and Program Director of Software Systems at Simon Fraser University's School of Computing Science in Surrey. His research focuses on energy-efficient software, multicore memory systems, and optimizing hardware/software interfaces for parallel programming. He holds a Ph.D. (2010) and M.S. (2006) in Computer Science from the University of Rochester, and a B.Eng. (2004) from the University of Madras. He teaches courses on parallel programming and energy-conscious software design. His research interests include synchronization mechanisms for domain-specific architectures, cache optimization, and FPGA-based acceleration. He has contributed to frameworks like Mu-grind for HLS-generated RTL instrumentation and TAPAS for parallel accelerator generation. Notable projects include RANGE-BLOCKS for synchronization in domain-specific systems and TapeFlow for gradient computation in neural networks. His work emphasizes real-time verification of autonomous systems and safety-critical trajectory planning for underwater vehicles. Shriraman collaborates closely with the Tangent Lab, exploring cutting-edge solutions in hardware-software co-design and embedded systems. His teaching and research bridge theoretical computer science with applied engineering challenges, addressing scalability, efficiency, and safety in modern computing systems.

Eugene Feinbergمشاهده پروفایل

استاد

• Markov Decision Processes
• Stochastic Optimization
• Inventory Control
• +۳ مورد دیگر

Eugene Feinberg is a Distinguished Professor in the Department of Applied Mathematics and Statistics at Stony Brook University's College of Engineering and Applied Sciences. He is renowned for his extensive contributions to Markov Decision Processes (MDPs), stochastic optimization, and inventory control. Research Interests: His work spans theoretical and applied aspects of Markov Decision Processes , stochastic optimization , inventory control , healthcare decision-making , and machine learning . He has particularly focused on solving complex decision-making problems under uncertainty, with applications ranging from operations research to medical decision-making. Scientific Awards: He has been honored with the title of Distinguished Professor , recognizing his outstanding contributions to his field. Advising and Grants: While specific details on students and grants are not provided, his prolific publication record and faculty status suggest active involvement in advising and securing research funding. Contact and Resources: His university webpage can be accessed at http://www.ams.sunysb.edu/~feinberg/ , and his Google Scholar profile is available at https://scholar.google.com/citations?user=LLt--pgAAAAJ&hl=en .

Qiaoning Carol Zhangمشاهده پروفایل

استادیار

• Human-AI Collaboration
• Human-Robot Interaction
• Human Factors in Automated Vehicles
• +۴ مورد دیگر

Qiaoning Carol Zhang serves as Assistant Professor of Human Systems Engineering within The Polytechnic School at Arizona State University's Ira A. Fulton Schools of Engineering. Her research investigates the critical intersection of human perception, social contexts, and emerging technologies including artificial intelligence, robotics, and automated vehicles, with emphasis on creating intuitive, user-friendly, and inclusive systems. Her academic foundation includes: Ph.D. in Information, University of Michigan (2023) M.S. in Industrial and Operations Engineering, University of Michigan (2018) B.S. in Industrial Engineering, Hunan University (2016) Dr. Zhang's research program centers on understanding how individual differences and social dynamics shape technology interactions. Key focus areas include Human-AI Collaboration , Human-Robot Interaction , Human Factors in Automated Vehicles , and User Experience Design . Her work employs interdisciplinary methodologies to ensure technology adapts to diverse user needs across complex socio-technical environments, particularly in transportation and healthcare robotics. Analysis of her 15 most recent publications (2021-2025) reveals dominant themes in trust dynamics within automated vehicles, with significant attention to explainable AI interfaces. Research consistently examines how voice characteristics (gender, similarity), explanation modalities, and individual differences (age, personality) impact cognitive and affective trust. Recent work extends to healthcare robotics for elderly populations using Kano model analysis to identify critical user requirements. No scientific awards are documented in the provided materials. Dr. Zhang actively recruits Ph.D. candidates and undergraduate/master's researchers with backgrounds in human-computer interaction, data science, and interdisciplinary fields (design, computer science, cognitive science). She emphasizes opportunities in transportation technology, healthcare robotics, AI, and UX research/design, requiring applicants to submit CVs, research statements, and representative work samples. While specific grants aren't detailed, her research scope indicates substantial funding in human factors and emerging technology domains. Her research team focuses on developing empathetic technology through projects examining trust calibration in automated vehicles and healthcare robot design for older adults. Current initiatives include voice interface optimization for diverse user groups and Kano model applications in home healthcare robotics, aiming to bridge technical capabilities with human-centered design principles.

Gerry Dozierمشاهده پروفایل

استاد

• Artificial Intelligence
• Cyber Security
• Computational Intelligence
• +۶ مورد دیگر

Gerry Dozier is the Charles D. McCrary Eminent Chair Professor in the Department of Computer Science and Software Engineering at Auburn University's College of Engineering. His research focuses on artificial intelligence, computational intelligence, cybersecurity, identity science, and cyber identity protection. He leads initiatives like the Center for Artificial Intelligence and Cybersecurity Engineering and contributes to Alabama's AI policy through the state commission. Dr. Dozier holds a Ph.D. from North Carolina State University and has pioneered work in adversarial machine learning, biometric security, and low-resource language NLP. Education: Ph.D. Computer Science, North Carolina State University (Raleigh) M.S. Computer Science, North Carolina State University (Raleigh) B.S. Computer Science, Northeastern Illinois University Research Themes: Combines AI with cybersecurity to address modern digital challenges. Specializes in adversarial attacks/defenses, biometric authentication systems, and ethical NLP applications in multilingual contexts. Active in developing tools for sentiment analysis in underrepresented languages and mitigating biases in automated systems. Impact: Spearheaded Auburn's AI@AU initiative with lecture series and forums. Collaborates internationally on facial recognition, malware detection, and medical AI applications like bacterial vaginosis diagnosis. His work bridges theoretical CS advancements with real-world security and ethical considerations. Labs/Teams: Directs Auburn's AI & Cybersecurity Engineering Center and contributes to interdisciplinary groups like the McCrary Institute for Cyber and Critical Infrastructure Security.

Claudia Wagnerمشاهده پروفایل

استاد

• Computational Social Science
• Algorithmic Fairness
• Digital Behavioral Data
• +۷ مورد دیگر

Claudia Wagner is a full professor for Applied Computational Social Sciences at RWTH Aachen University and the Scientific Director of the Computational Social Science department at GESIS—Leibniz Institute for the Social Sciences. She is also an External Faculty member at the Complexity Science Hub Vienna. Her work bridges computer science and the social sciences to study algorithmic systems and their societal impacts. Her research focuses on socio-technical phenomena such as inequality, sexism, and perception bias in algorithmically infused societies. She investigates methodological challenges in using digital behavioral data to study human behavior, attitudes, and group dynamics. Her interests span computational social science, algorithmic fairness, network science, and AI ethics. The analysis of her recent publications reveals a strong emphasis on bias, fairness, and methodological rigor in digital data analysis. Her work spans AI psychometrics, gender inequality in online platforms, and validation frameworks for digital traces. She frequently publishes in top-tier venues such as Nature , Science , and AAAI conferences. DOC-fFORTE fellowship from the Austrian Academy of Sciences Four best paper awards at international conferences (ICWSM, CSCW, WWW, AAAI) Associate Editor, EPJ Data Science Steering Committee Member, International AAAI Conference on Web and Social Media Board Member, International Society for Computational Social Science Claudia Wagner has led and co-led substantial research projects funded by national and international agencies. She mentors a diverse group of PhD students working on topics like algorithmic bias, data quality, and dehumanization. She has organized training events such as the CSS Methods Summer School and delivered keynotes globally on inequality and computational social science. She leads the Computational Social Science department at GESIS and collaborates with interdisciplinary teams at RWTH Aachen and the Complexity Science Hub. Her group develops tools for measuring algorithmic impacts and visualizing disparities in socio-technical systems, such as the 'Planets of Disparity' dashboard.

Andrea Groverمشاهده پروفایل

دانشیار

• Citizen Science
• Information Systems
• Open Collaboration Systems
• +۳ مورد دیگر

Dr. Andrea Grover is an Associate Professor in the Department of Information Systems and Quantitative Analysis at the University of Nebraska Omaha’s College of Information Science & Technology. Her research focuses on citizen science, technology design, and collaboration systems in data-intensive environments. She holds a Ph.D. in Information Science & Technology from Syracuse University, an MS in Information from the University of Michigan, and a BA in Mathematics from Alma College. Her research interests include organizational impacts of technology, open collaboration frameworks, and ethics in information systems. She teaches courses on management and IT ethics, employing ungrading techniques to enhance student engagement. Notable contributions include work on citizen science data quality, cyber-security tools leveraging crowdsourcing, and barriers in STEM education equity. Dr. Grover has been recognized with the 2022 Rising Star Distinguished Ecologist award and serves on editorial boards (e.g., Frontiers in Ecology) and conference committees (e.g., ACM CSCW DEI Co-chair). She has secured grants such as the NSF-funded “Streamlining Embedded Assessment to Understand Citizen Scientists' Skill Gains” (2017–2019) and contributed to media discussions on citizen science via National Public Radio. Her recent publications explore hybrid human-AI tools, agile citizen science methodologies, and systemic barriers in education. She actively participates in interdisciplinary initiatives, bridging technology, ecology, and social sciences to advance participatory research practices.

Wesley Willettمشاهده پروفایل

دانشیار

• Information visualization
• Human-computer interaction
• New media
• +۳ مورد دیگر

Wesley Willett is an Associate Professor in the Department of Computer Science at the University of Calgary, holding the NSERC CRC II Chair in Visual Analytics. His primary research focuses on information visualization, human-computer interaction, and new media applications. He leads the Data Experience Lab and Interactions Lab, exploring innovative methods for data representation and interaction in augmented/virtual reality environments. Education includes a B.S. in Computer Science from the University of Colorado (2006) and a Ph.D. in Computer Science from UC Berkeley (2012). His work bridges technical innovation with user-centered design principles, emphasizing ethical considerations in data visualization and inclusive representation. Key research contributions include: spatial visualization techniques for large environments, gesture-based interfaces for AR/VR, and physical data representations through projects like Cetonia (swarm robotics visualization) and Data Embroidery. His work has been recognized with Best Paper awards at CHI 2015 and Pervasive 2010. Current research emphasizes immersive analytics, wearable visualization systems, and demographically diverse anthropographics. He collaborates with urban designers, neurologists, and environmental scientists to apply visualization in diverse domains like epilepsy surgery planning and air quality monitoring.

Hassan Z. Ashtianiمشاهده پروفایل

دانشیار

• Machine Learning Theory
• Privacy-Preserving Algorithms
• Gaussian Mixture Models
• +۵ مورد دیگر

Hassan Z. Ashtiani is an Associate Professor in the Department of Computing and Software within the Faculty of Engineering at McMaster University. His academic profile shows consistent engagement in both teaching and research activities, with evidence of active participation in major machine learning conferences and journals through 2025. Dr. Ashtiani's research focuses on the theoretical foundations of machine learning, with particular expertise in privacy-preserving algorithms, Gaussian mixture models, and adversarial robustness. His work bridges statistical learning theory with practical algorithm design, often addressing fundamental questions about sample complexity and computational efficiency in learning systems. A significant portion of his recent work explores the intersection of differential privacy with statistical learning, developing methods for private density estimation and distribution learning. Analysis of his publication record reveals a strong trend toward increasingly sophisticated theoretical frameworks for private and robust learning. His work consistently appears in top-tier venues including NeurIPS, ICML, COLT, and ALT, with recent contributions extending into agnostic private density estimation and robust learning with tolerance. The research demonstrates progression from foundational work on nearest neighbor search and clustering algorithms toward more complex problems in private learning of high-dimensional distributions. Dr. Ashtiani teaches across multiple levels of computer science education, including undergraduate courses in Automata and Computability (COMPSCI 2AC3) and Principles of Programming (COMPSCI 2S03), as well as graduate-level courses such as Fundamentals of Machine Learning (COMPSCI 4ML3) and Theoretical Foundations of Unsupervised Learning (CAS 775). His teaching portfolio shows consistent involvement in machine learning education since at least 2019, with evidence of teaching multiple sections each academic year. His scholarly impact is reflected in mentions across 3 news outlets, reference in 1 policy source, engagement from 7 X users, and 90 readers on Mendeley, suggesting growing recognition of his contributions to theoretical machine learning.

Sam Emaminejadمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Wearable Technology
• Microfluidics
• +۳ مورد دیگر

Sam Emaminejad is an Associate Professor in the Department of Electrical and Computer Engineering at the Henry Samueli School of Engineering and Applied Science, University of California Los Angeles (UCLA). His research focuses on developing advanced wearable bioelectronic systems for continuous, noninvasive health monitoring and personalized therapeutics. Key Research Areas: Biomarker detection via flexible sensors Microfluidic and ferrobotic systems Stress and drug level monitoring Biodegradable and breathable wearable materials Recent Trends: Analysis of sweat and interstitial fluids using microneedles, aerogel skins, and programmable microfluidics. Machine learning integration for physiological evaluation is prominent. Awards & Collaborations: While specific awards aren't listed, he collaborates with major UCLA Health and Engineering faculty, including Ali Khademhosseini and Dino Di Carlo, on projects funded by NIH T32 grants and institutional fellowship programs. Grants & Labs: Leads projects in NIH-funded wearable sensor research, including the development of autonomous systems for cystic fibrosis and glucose monitoring. His lab explores ferrobotic swarms and hydrogel-based interfaces for clinical and consumer applications.

• Artificial Intelligence
• Legal Technology
• Dispute Resolution
• +۳ مورد دیگر

Professor John Zeleznikow is an Honorary Associate at La Trobe University's Law School, with a distinguished career spanning 49 years across multiple institutions including the University of Edinburgh and Victoria Business School. His research focuses on AI applications in legal decision-making, dispute resolution, and autonomous vehicle technology. He has secured over $8M in research grants and supervised 20 PhD graduates. Key projects include the Split-Up system (used in high-profile divorce cases like Prince Charles and Lady Di) and Family-Winner software, which won an ABC TV innovation award. His work bridges law, technology, and ethics, with publications in leading journals like the Harvard Negotiation Law Review and Artificial Intelligence and Law . Recent research explores AI-driven online dispute resolution (ODR), autonomous vehicle regulation, and the ethical implications of technology in legal systems. He advocates for transparent, user-centric legal tech solutions to enhance access to justice and improve decision-making processes.

• Computer Science
• Social Sciences
• Geography and Planning
• +۳ مورد دیگر

Dr. Jeffrey Morgan is a Researcher at Cardiff University's School of Social Sciences, specializing in multidisciplinary research at the intersection of computer science, social science, and geography. His work emphasizes human-computer interaction, visualization, and big data analytics. He holds a Research Software Engineer role, combining technical expertise with academic inquiry. Key research interests include AI-driven patent analysis, IoT applications in rural citizen science, and geospatial Twitter demographics. He has contributed to studies on Hadoop infrastructure optimization and social media conflict detection, often collaborating with institutions like Xiamen University and the University of Bremen. His publications span topics like energy-efficient big data processing, digital geography of Welsh identity, and scalable social media analysis frameworks. Notable projects include COSMOS (a cloud-based social media analysis platform) and studies on post-devolution cultural narratives in Wales. Award-winning work includes computational Twitter analysis for detecting online community tensions and geotagging behavior patterns. His research often bridges technical innovation with societal impact, addressing challenges in rural technology deployment and digital sociology.

Gunes Acarمشاهده پروفایل

استادیار

• Web Security
• Privacy
• Online Tracking
• +۳ مورد دیگر

Güneş Acar is a tenured Assistant Professor in the Digital Security group at Radboud University's Faculty of Science. He is also affiliated with iHub, Radboud's interdisciplinary research hub on digitalization and society. His research focuses on security and privacy threats from websites, mobile apps, and IoT devices, with special emphasis on online tracking mechanisms, anonymous communication networks like Tor, and deceptive design patterns. Dr. Acar completed his PhD at KU Leuven under the supervision of Claudia Diaz and Bart Preneel. Prior to joining Radboud University, he was a Postdoctoral Research Fellow at KU Leuven's COSIC group and a Postdoctoral Research Associate at Princeton University's Center for Information Technology Policy. His research spans web security, privacy, online tracking, IoT security, Tor network analysis, and dark patterns. He investigates how websites, mobile apps, and IoT devices compromise user privacy through various tracking mechanisms and deceptive interface designs. His work combines large-scale measurements with user studies to understand both technical vulnerabilities and their real-world impact on users. Dr. Acar's publications reveal an evolving research trajectory from foundational web tracking mechanisms to increasingly sophisticated privacy threats. His work has expanded from browser fingerprinting to IoT privacy, children's online safety, and manipulative design patterns in subscription interfaces. A consistent theme across his research is the examination of how third-party trackers operate and circumvent privacy protections. 2022 CNIL-Inria Award for Privacy Protection (for Leaky Forms paper) Top Reviewer Award, Privacy Enhancing Technologies Symposium (2022) Future of Privacy Forum's Annual Privacy Papers for Policymakers Award (2020) Runner-up for multiple Caspar Bowden Awards for Outstanding Research in Privacy Enhancing Technologies Dutch Research Council (NWO) Vidi Grant (2025-2030) for "A Web Security and Privacy Observatory" Dr. Acar actively supervises PhD students including Zahra Moti, Tim Vlummens, and Luqman Zagi, with Asuman Senol recently completing her PhD in 2024. He has secured significant research funding including the NWO Vidi Grant and a project grant from armasuisse for the Mobile Web Inspector project. His research has influenced policy discussions with organizations including the OECD, US Federal Trade Commission, and European consumer protection authorities. As part of the Digital Security group at Radboud University, Dr. Acar contributes to a vibrant research ecosystem focused on practical security and privacy solutions. His work bridges technical security research with human-centered perspectives, often collaborating across disciplines to address complex privacy challenges in real-world contexts.